Search Results (288)

In this research project a large linear electromagnetic actuator (LLEA) was designed and manufactured. The electromagnetic performance was published in previous works, but in this paper we focus on the technological challenges related to the manufacturing in particular. This LLEA was based on the magnet-free switched-reluctance principle, having six effective energised stator “teeth” and four passive mover parts (4:6 ratio). Various aspects and challenges encountered during the manufacturing, transport, and assembly are discussed. Thermal expansion of steel contributed to the decision of the modular design, with each module having 1.3 m in length, with a 2 mm longitudinal dilatation gap. The initial prototype was tested with a 10.6 m length, with plans to extend the test track to 60 m, which was fully achievable due to the modular design and required 29 tons of electrical steel to be built. The stator laminations were cut by a bespoke progressive tool with stamping, and other parts by a CO₂ laser. Mounting was based on welding (back of the stator) and clamping plates (through insulated bolts). The linear longitudinal force was on the order of 8 kN, with the main air gap of 7.5–10 mm on either side of the mover. The lateral forces could exceed 40 kN and were supported by appropriate construction steel members bolted to the concrete floor. The overall mechanical tolerances after installation remained below 0.5 mm. The technology used for constructing this prototype demonstrated the cost-effective way for a semi-industrial manufacturing scale. Full article

Small towns in mountainous regions face significant challenges in formulating effective landscape zoning strategies due to pronounced landscape fragmentation, which is driven by both the dominance of large-scale forest resources and the lack of coordination between administrative planning departments. To tackle this problem, this study focused on Yuqian, a quintessential small mountainous town in Hangzhou, Zhejiang Province. The town’s layout was divided into a grid network measuring 70 m × 70 m. A two-step cluster process was employed using ArcGIS and SPSS software to analyze five landscape variables: altitude, slope, land use, heritage density, and visual visibility. Further, eCognition software’s semi-automated segmentation technique, complemented by manual adjustments, helped delineate landscape character types and areas. The overlay analysis integrated these areas with administrative village units, identifying four landscape character types across 35 character areas, which were recategorized into four planning and management zones: urban comprehensive service areas, agricultural and cultural tourism development areas, industrial development growth areas, and mountain forest ecological conservation areas. This result optimizes the current zoning types. These zones closely match governmental sustainable development zoning requirements. Based on these findings, we propose integrated landscape management and conservation strategies, including the cautious expansion of urban areas, leveraging agricultural and cultural tourism, ensuring industrial activities do not impact the natural and village environment adversely, and prioritizing ecological conservation in sensitive areas. This approach integrates spatial and administrative dimensions to enhance landscape connectivity and resource sustainability, providing key guidance for small town development in mountainous regions with unique environmental and cultural contexts. Full article

The Norwegian construction sector has long struggled with conflict, particularly in large-scale and complex projects, where adversarial practices, rigid procurement systems, and insufficient early collaboration are common. This study explores how partnering contracts, which are collaborative delivery models designed to align stakeholder interests, affect conflict dynamics in real-world settings. Employing a mixed-methods approach, it combines semi-structured interviews with 21 experienced Norwegian construction professionals and a structured survey of 33 industry experts. The findings reveal that partnering can foster trust, improve communication, and reduce adversarial behavior through mechanisms such as early contractor involvement, joint goal setting, and open dialogue. However, participants also identified critical risks: superficial collaboration rituals, ambiguous roles, and unresolved structural inequalities that can exacerbate tensions. Importantly, the study emphasizes that partnering success depends less on the contract itself and more on cultural alignment, stakeholder competence, and long-term relational commitment. These insights contribute to a more nuanced understanding of how collaborative contracting influences conflict mitigation in the Norwegian construction sector. Full article

The development of slow-release fertilizers (SRFs) based on production residues is a promising strategy to improve nutrient use efficiency and promote circular economy practices in agriculture. In this study, a series of experimental formulations were designed and tested using pumice scraps, liquid and dried blood, and bone meal, aiming at producing sustainable and low-cost N-P-K SRFs. These were processed through mixing and granulation, both in the laboratory and on a semi-industrial scale. The formulations were evaluated through release tests in 2% citric acid solution simulating the acidic conditions of the rhizosphere, and in acetic acid to assess potential nutrient leaching under acid rain conditions. The results showed a progressive cumulative release of macronutrients (NPKs), ranging from approximately 8% at 24 h to 73% after 90 days for the most effective formulation (WBF6). Agronomic trials on lettuce confirmed the effectiveness of WBF6, resulting in significant biomass increases compared with both the untreated control and a conventional fertilizer. The use of livestock waste and minerals facilitated the development of a scalable product aligned with the principles of sustainable agriculture. The observed release behavior, combined with the simplicity of production, positions these formulations as a promising alternative to conventional slow-release fertilizers. Full article

The date palm industry is a vital pillar of agricultural economies in arid and semi-arid regions; however, it remains vulnerable to challenges such as pest infestations, post-harvest diseases, and limited access to real-time monitoring tools. This study applied the baseline YOLOv11 model and its optimized variant, YOLOv11-Opt, to automate the detection, classification, and monitoring of date fruit varieties and disease-related defects. The models were trained on a curated dataset of real-world images collected in Saudi Arabia and enhanced through advanced data augmentation techniques, dynamic label assignment (SimOTA++), and extensive hyperparameter optimization. The experimental results demonstrated that YOLOv11-Opt significantly outperformed the baseline YOLOv11, achieving an overall classification accuracy of 99.04% for date types and 99.69% for disease detection, with ROC-AUC scores exceeding 99% in most cases. The optimized model effectively distinguished visually complex diseases, such as scale insert and dry date skin, across multiple date types, enabling high-resolution, real-time inference. Furthermore, a visual analytics dashboard was developed to support strategic decision-making by providing insights into production trends, disease prevalence, and varietal distribution. These findings underscore the value of integrating optimized deep learning architectures and visual analytics for intelligent, scalable, and sustainable precision agriculture. Full article

The present study examined the drying kinetics of two-phase olive pomace (OP) using near-infrared (NIR) thin layer intermittent drying at 70–140 °C. For the first time, this approach was combined with color, bioactive compound retention and antioxidant activity assessment. Among tested models, the Midilli’s semi-empirical model best described the drying behavior (r² ≥ 0.99839, RMSE ≤ 0.01349). Effective diffusivity ranged from 1.417 × 10⁻⁹ to 5.807 × 10⁻⁹ m²/s, and activation energy was calculated at 23.732 kJ/mol. Drying at 140 °C reduced time by 68% compared to 70 °C. The corresponding sample had the highest total phenolics content, antioxidant activity (DPPH^●, CUPRAC assays) and triterpenic acid (maslinic, oleanolic) content, and a significant amount of hydroxytyrosol, despite the increased sample browning. Compared to oven-drying (140 °C), NIR was equal or better and 3.2-fold faster. The same was evidenced compared to freeze-drying, except for tyrosol recovery (1.2-fold lower in NIR). These findings were obtained using two different OP industrial samples. Given that NIR is already used industrially for food drying, the present study offers proof-of-concept for its application as a rapid and eco-friendly pretreatment of OP for food and feed uses. However, scalability challenges and the limitations of semi-empirical modeling must be addressed in the future to support industrial-scale implementation. Full article

This study describes the step-by-step development of a simplified system which can be implemented in industrial facilities with the help of their own surplus of plastic waste, mainly packaging waste, to reach a level of energy autonomy or semi-autonomy. This waste is converted to about 57,500 L of synthetic pyrolysis oil, which can then be used to power industries, being fed into a Combined Heat and Power system. To achieve this goal, the design has hydrocarbon stability at elevated temperature and restricted oxygen exposure, so that they can be converted to new products. Pyrolysis is a key process which causes thermo-chemical changes—ignition and vaporization. The research outlines the complete process of creating a basic small-scale pyrolysis system which industrial facilities can use to generate energy from their plastic waste. The proposed unit processes 360 tons of plastic waste yearly to produce 160 tons of synthetic pyrolysis oil which enables the generation of 500 MWh of electricity and 60 MWh of heat. The total investment cost is estimated at EUR 41,000, with potential annual revenue of up to EUR 45,000 via net metering. The conceptual design proves both environmental and economic viability by providing a workable method for decentralized waste-to-energy solutions for Small and Medium-sized Enterprises. Full article

The changing climate poses a significant challenge to the dairy industry, particularly in Punjab’s Faisalabad region, a central milk production hub. Rising temperatures and humidity exacerbate heat stress, endangering rural livelihoods. This study quantifies the impacts of these climatic stressors on milk yield, evaluates smallholder farmers’ perceptions of climate risks, and projects future losses to guide adaptive policymaking. By integrating Likert-scale surveys of 450 dairy farmers with advanced panel regression models (including fixed and random effects) and a dynamic panel generalized method of moments (GMM) approach for forecasting, we analyzed eight years of milk production and climate data (2017–2024) under IPCC scenarios (+2 °C, +10% humidity). The results revealed significant declines: a 1 °C temperature increase reduced milk yields by 1.72 L per month (p < 0.01), while a 1% rise in humidity decreased output by 0.59 L per month (p < 0.01). Compounded losses under combined stressors reached 2.25 L per month, with hotter regions (Faisalabad’s semi-arid zone) experiencing the steepest declines. Farmers’ perceptions are closely aligned with empirical trends, identifying heat humidity interactions as the most critical risks. To mitigate these losses, adaptive strategies such as heat-resistant cattle breeds, humidity-responsive cooling systems, and targeted financial support for smallholders are critical. This study connects farmers’ insights with econometric modeling to provide practical strategies to enhance resilience in Punjab’s dairy sector. Full article

With the continuous advancement of industrialization and intelligentization, stereo-vision-based measurement technology for large-scale components has become a prominent research focus. To address weak-textured regions in large-scale component images and reduce mismatches in stereo matching, we propose a cross-scale multi-feature stereo matching algorithm. In the cost-computation stage, the sum of absolute differences (SAD), census, and modified census cost aggregation are employed as cost-calculation methods. During the cost-aggregation phase, cross-scale theory is introduced to fuse multi-scale cost volumes using distinct aggregation parameters through a cross-scale framework. Experimental results on both benchmark and real-world datasets demonstrate that the enhanced algorithm achieves an average mismatch rate of 12.25%, exhibiting superior robustness compared to conventional census transform and semi-global matching (SGM) algorithms. Full article

Lachancea thermotolerans help increase the acidity of wines by producing L-lactic acid, which can serve as a strategy to mitigate the decrease in total acidity in wines promoted by climate change. The aim of the present paper is to test the capability of wine bioacidification of wild strains isolated from Rioja AOC. For this purpose, L. thermotolerans strains isolated from musts were used in mixed fermentation (co-inoculation and sequential inoculation) with Saccharomyces cerevisiae to determine the fermentation performance and L-lactic acid production, in both laboratory scale and pilot scale. Fermentation kinetics was evaluated, in addition to the final wine chemical composition and organoleptical properties. The results indicated that the isolated strains produced L-lactic acid; these effects were dependent on the strain and the inoculation strategy, being higher the effect in sequential inoculation (9.20 g/L) than in co-inoculation. This L-lactic acid production capacity was maintained at a pilot scale (4.65 g/L), in which the acidity increase was perceptible in the sensorial analysis, and an ethanol concentration decrease was also reported. The wine acidification depends on the appropriate selection of the strains, the inoculation procedure, the yeast adaptation to media, and competence with other yeast species present in the fermentation broth. The wild L. thermotolerans Lt97 strain could be used as a bioacidification tool for wines affected by climate change. Full article

Semi-continuous casting is an important method for the large-scale production of high-strength conductive copper-iron (Cu-Fe) alloys in the future. However, serious peeling defects were found on the surface of cold-rolled strips during industrial trials. Due to the multi-step complexity of the manufacturing process (from casting to final product), identifying the root cause of defect formation remains challenging. X-ray computed tomography (X-CT) was used to quantitatively characterize the pores and defects in the horizontal continuous casting Cu-Ni-Sn slab, the semi-continuous casting Cu-Fe alloy slab, and the hot-rolled slab of Cu-Fe, and the relationship between the defect characteristics and processes was analyzed. The results showed that the internal defect sphericity distribution of the Cu-Fe alloy slab after hot rolling was similar to that of the reference Cu-Ni-Sn slab. The main difference lies in the low sphericity range (<0.4). The volume of pore defects inside the Cu-Fe alloy after hot rolling was significantly larger than in the reference sample, with a 52-fold volume difference. This phenomenon may be the source of surface-peeling defects in the subsequent cold-rolling process. The occurrence of internal defects in the Cu-Fe alloy is related to both the composition characteristics and casting processes of the Cu-Fe alloy; on the other hand, it is also related to the hot-rolling process. Full article

Increased emissions of carbon dioxide (CO₂) from industrial activities are the main cause of the growing problem of global warming and climate change, highlighting the needs for efficient CO₂ capture and storage (CCS) techniques. The present work aims to investigate the possibility of CO₂ sequestration using sodium hydroxide (NaOH) in a semi-batch column with an integrated gas lift tower and an ultra-micro bubbles generator, a novel setup designed to enhance mass transfer rates and capture efficiency. Unlike the previously reported setups, our system achieves a 50% faster capture rate with improved mass transfer, enhanced gas-liquid interaction and higher removal efficiency due to finer bubble dispersion, as confirmed by experimental findings. Preliminary tests to ascertain the effectiveness of CO₂ removal were carried out across various CO₂ gas flow rates (3, 5, 7 L/min), NaOH volumes (2, 3, 4 L) and concentrations (0.1, 0.2, 0.3 M). The results indicated that both gas flow rate and NaOH concentration have profound impacts on the CO₂ capture rate. Increasing either of these parameters, or using low concentrations of NaOH, leads to a rapid drop in pH due to a faster rate of neutralization and the formation of carbonic acid (H₂CO₃), a weak acidic solution. For instance, with 0.1 M NaOH and 2 L volume, the pH decreased from 13.07 to 7.02 within 1.5 min at gas flow rate of 7 L/min, while with 0.3 M NaOH, pH reduced to 7.3 after 6 min. Higher volumes and concentrations of NaOH caused a decrease in the capture rate of CO₂ due to reversed reaction with formed sodium carbonate. For instance, with 0.3 M NaOH and 4 L volume, the pH reduced from 13.58 to 8 after 5 min at 7 L/min gas flow rate. Scaling up to a 100 L semi-batch column with an ultra-fine micro bubble generator, as a new approach, reduced the time taken by half in the capture of CO₂. Additionally, the study also investigated the comparison of tap versus deionized water in CO₂ capture reaction. The results demonstrated that dissolved minerals in tap water, particularly Ca²⁺ and Mg²⁺ ions, affected precipitate formation and capture efficiency differently than deionized water, offering practical insights for CCS in varied water sources. Full article

In recent years, consumer demand for animal-friendly production systems has driven the livestock industry to improve welfare standards. Protocols have been developed for different species such as calves, pigs, laying hens, and broilers to assess farms, compare practices, and establish a baseline for optimal welfare. However, despite their undoubted importance and presence on farms, ostriches are not included in these protocols. This study aims to develop a protocol for the welfare assessment of ostriches reared in intensive and semi-intensive systems using different indicators, which is feasible and time efficient. The protocol developed combines animal-based measures (physiological, appearance, and behavioral) with resource-based and management-based measures (management and environmental). Specifically, the ostrich welfare assessment protocol (OWAP) included 41 non-invasive measures: 14 animal-based, 12 resource-based, and 15 management-based. These measures were selected for their relevance, reliability, and feasibility. Each parameter is scored on a graded scale based on its condition, and the scores are aggregated to determine the overall welfare status of the ostriches. A threshold is set to classify welfare as acceptable, suboptimal, or unacceptable. Out of a total score of 95 (64 for indirect measures and 31 for direct measures), a score <32 was considered unacceptable, between 32–63 suboptimal, and >63 optimal. This scoring system provides a systematic, objective approach to assessing ostrich welfare under different husbandry conditions. Full article

Cellulose, a widely abundant natural polymer, is well recognized for its remarkable properties, such as biocompatibility, degradability, and mechanical strength. Conductive hydrogels, with their unique ability to conduct electricity, have attracted significant attention in various fields. The combination of cellulose and conductive hydrogels has led to the emergence of cellulose-based conductive hydrogels, which show great potential in flexible electronics, biomedicine, and energy storage. This review article comprehensively presents the latest progress in cellulose-based conductive hydrogels. Firstly, it provides an in-depth overview of cellulose, covering aspects like its structure, diverse sources, and classification. This emphasizes cellulose’s role as a renewable and versatile material. The development and applications of different forms of cellulose, including delignified wood, bacterial cellulose, nanocellulose, and modified cellulose, are elaborated. Subsequently, cellulose-based hydrogels are introduced, with a focus on their network structures, such as single-network, interpenetrating network, and semi-interpenetrating network. The construction of cellulose-based conductive hydrogels is then discussed in detail. This includes their conductive forms, which are classified into electronic and ionic conductive hydrogels, and key performance requirements, such as cost-effectiveness, mechanical property regulation, sensitive response to environmental stimuli, self-healing ability, stable conductivity, and multifunctionality. The applications of cellulose-based conductive hydrogels in multiple areas are also presented. In wearable sensors, they can effectively monitor human physiological signals in real time. In intelligent biomedicine, they contribute to wound healing, tissue engineering, and nerve regeneration. In flexible supercapacitors, they offer potential for green and sustainable energy storage. In gel electrolytes for conventional batteries, they help address critical issues like lithium dendrite growth. Despite the significant progress, there are still challenges to overcome. These include enhancing the multifunctionality and intelligence of cellulose-based conductive hydrogels, strengthening their connection with artificial intelligence, and achieving simple, green, and intelligent large-scale industrial production. Future research directions should center around exploring new synthesis methods, optimizing material properties, and expanding applications in emerging fields, aiming to promote the widespread commercialization of these materials. Full article

Cytochrome P450 enzymes (CYPs) are versatile heme-containing monooxygenases involved in the metabolism of endogenous and exogenous compounds, as well as natural product biosynthesis. Their ability to catalyze regio- and stereoselective oxidation reactions makes them valuable in pharmaceuticals, fine chemicals, and biocatalysis. However, wild-type CYPs suffer from low catalytic efficiency, limited substrate specificity, and instability under industrial conditions. Recent advances in protein engineering—rational design, semi-rational design, and directed evolution—have enhanced their activity, stability, and substrate scope. These strategies have enabled CYPs to be engineered for applications like C–H functionalization, carbene transfer, and complex molecule biosynthesis. Despite progress, challenges remain in optimizing efficiency, expanding substrate ranges, and scaling production for industrial use. Future directions include integrating CYPs with other biocatalysts, improving high-throughput screening, and applying machine learning to enzyme design. This review highlights recent developments and the promising future of engineered CYPs in sustainable chemistry, drug development, and high-value chemical production. Full article